The deepening productivity crisis in the pharmaceutical industry, the high cost to the pharmaceutical industry of introducing new drugs to the market, partly because of expenses related to Phase I, II and III clinical trials, as well as late stage failures for many drug candidates have spurred intense across-the-board activity around biomarker discovery and validation. Biomarkers, defined by the FDA as a characteristic that is objectively measured and evaluated as an indicator of normal biologic or pathogenic processes or pharmacological responses to a therapeutic intervention, are being sought actively to help make early and cost-effective “go/no-go” decisions on drugs, for patient stratification, clinical trial analysis, and finding niche markets (e.g., sub-population of patients who respond to drugs or in whom no drug-related toxicity is seen) for new drugs under development. In addition, the FDA has recently recommended that validated or investigational biomarker data be included in IND and NDA packages. These are powerful drivers for the biomarker market, whose size is estimated at $428 millions in 2005, and is growing at 20 percent per year.
The use of biomarkers is rapidly gaining momentum in the pharmaceutical industry and in the medical management of patients. Current methods for identifying biomarkers involve the use of biochemical assays for identifying “functional” biomarkers, such as genes or protein arrays or metabolite analysis. The use of biochemical assays in this context requires probing for functional alterations in genes and proteins, the need for a priori knowledge of their function, as well as extensive assay development and optimization.
While there has been an explosion of biomarker discovery efforts utilizing genomics, proteomics and metabolomics, these technologies also focus only on functional biomarkers. With many diseases, the presence of observable functional biomarkers often occurs late in the disease state. As such, preventive measures for these diseases may be ineffective when developed in connection with the management of the disease, or in early evaluation of drug efficacy.
Contributions towards understanding ultrastructural morphology have been made in recent years. Such an approach focuses on the ultra-structural differences in the biological samples that can occur much earlier in the diseased state, even before functional differences are observable. Since these target structures typically range from between about 5 nanometers (nm) and 1 micrometer, one approach to visualize them is through the use of conventional transmission electron microscopy (TEM). However, the use of conventional TEM has some critical limitations. For example (i) the high vacuum used in TEM removes solvent, leaving behind structures that are quite different from those present in the original solution, (ii) adequate contrast between the sample features and background is usually not available, necessitating the use of stains (the addition of stains, which usually are heavy metal salts, can cause dramatic changes in aggregate morphology), and (iii) the exposure of the sample to the electron beam often damages the sample.
Accordingly, it would be desirable to provide an approach that can generate substantially artifact-free images of structural biomarkers of a cell or biological sample without compromising the integrity of the biomarkers in the sample.